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Abstract

Background

Audit is a fundamental part of antimicrobial stewardship, but this has traditionally been labour-intensive. The advent of fully electronic records (EPIC) at Cambridge University Hospitals (CUH) presents novel opportunities for large-scale automated data analyses and feedback. We developed and validated an algorithm to audit the appropriateness of prescriptions initiated for presumed community-acquired pneumonia (CAP).

Methods

We developed an algorithm that extracts prescription and clinical data from EPIC, calculates CURB-65 scores, and assesses the appropriateness of antibiotics with an indication of CAP against Trust guidelines based on predefined rules. Clinical data included age, gender, blood results, vital signs, NEWS-2 score, MRSA status, penicillin allergy and pregnancy status. Prescriptions were limited to 48 hours from admission. The accuracy of the algorithm was validated in a representative sample of 30 patients.

We present data on all prescriptions initiated for CAP admitted to CUH between September 2018 and June 2019.

Results

On validation, the algorithm calculated the CURB-65 score with an accuracy of 97% and correctly categorised antibiotic appropriateness in 98.5% of cases. Only 15% of patients had a CURB-65 score documented in the notes.

The algorithm evaluated 4,307 prescriptions in 2,198 patients. Appropriateness was significantly better in CURB-65 scores of 2-5 (83.7%) versus 0-1 (33.5%) largely due to over-prescription of co-amoxiclav in the latter.

Conclusion

This algorithm enables large-scale analysis of prescriptions initiated for CAP with high accuracy automating the audit cycle. An automatically calculated CURB-65 score has the potential to reduce over-prescribing of co-amoxiclav and should be evaluated in the future.

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/content/journal/acmi/10.1099/acmi.fis2019.po0134
2020-02-28
2020-06-04
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http://instance.metastore.ingenta.com/content/journal/acmi/10.1099/acmi.fis2019.po0134
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